Laws

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LAWS, RHODIAN, maritime. law. A code of laws adopted by the people of Rhodes, who had, by their commerce and naval victories, obtained the sovereignty of the sea, about nine hundred. years before the Christian era. There is reason to suppose this code has not been transmitted to posterity, at least not in a perfect state. A collection of marine constitutions, under the denomination of Rhodian Laws, may be seen in Vinnius, but they bear evident marks of a spurious origin. See Marsh. Ins. B. 1, c. 4, p. 15; this Dict. Code; Laws of Oleron; Laws of Wisbuy; Laws of the Hanse Towns.

References in periodicals archive ?
Thus, Amdahl's Law can calculate the upper bound of the parallel program speedup.
Nguyen, "Amdahl's law for multithreaded multicore processors," Journal of Parallel and Distributed Computing, vol.
Also, the total execution time T(f, n, [p.sub.app]) with diverse numbers of cores is able to be estimated by using Amdahl's law. It should also be noted that the execution time depends on the compression parameter q.
* Find articles and papers that mention Amdahl's laws, including the original articles.
Section 2 presents an overview on Amdahl's law. In Section 3, we briefly describe the different types of multicore architectures.
Technically, discussions on a migration option can be couched in terms of Amdahl's law: keep the sequential sections of code in a common language such as C or C++ and express the parallel sections so they can be migrated should it prove necessary to do so in the future.
In the late 1980s, key concerns included whether Amdahl's Law would limit to 100 or so the number of processors that can be used efficiently (see the sidebar Promise and Limits of Amdahl's Law and Moore's Law).
Amdahl's Law was a state-of-the-art analytical model that guided software developers to evaluate the actual speedup that could be achieved by using parallel programs, or hardware designers to draw much more elaborate microarchitecture and components.
In a nutshell, this is the argument behind Amdahl's law that notes the speedup of a program using multiple processors will be limited by the rime spent in any sequential portions of the code.
These computers let programmers dodge hard problems by running them on one processor and blaming Amdahl's law for the resulting poor performance.
The performance obtained by this typical parallelization is limited according to Amdahl's law [8][9][10][11].
A danger with parallel programming, according to Amdahl's law [1], is that there are sequential bottlenecks which prohibit parallelization.